When Manufacturing Expertise Walks Out the Door

A 30-year veteran plant manager retires.  

With them goes the ability to detect a failing pump by the pitch of its hum, the intuition that a valve is stuck and extending cleaning cycles, and the undocumented recipe adjustments they made when humidity was running high inside the plant.

Knowledge loss in manufacturing and especially the food and beverage industry is a quiet crisis.

We've witnessed this challenge at every facility we consult with on Clean-in-Place optimization and more efficient product changeovers.

At one beverage facility we work with, a longtime operator could tell when a cleaning cycle was complete by looking at foam through the sight glass. He didn't need a timer or know conductivity numbers — decades of pattern recognition. When he left, the team added fifteen extra minutes to every cycle as a buffer... just to be sure that the line is clean.  

Do the math: across three lines running four cycles daily; that adds up to over 700 hours of lost production time per year.

This is how inefficiency becomes institutionalized.

The post-Covid Great Retirement and impact on F&B factories

The Great Retirement — a byproduct of COVID — drained manufacturing of home-grown expertise, and the trend shows no signs of slowing down. Food and beverage facilities continue to lose the veteran workers who kept production lines running smoothly for decades.

40% Turnover in Year One

In some food and beverage processing facilities, 40 percent of new hires leave within their first year. Knowledge transfer has become deeply problematic because the traditional apprenticeship model has largely disappeared. New workers aren't being systematically trained or given compelling reasons to build long-term careers in manufacturing.

The problem compounds when you look at the equipment itself. Manufacturing shop floors have aged along with the workforce — pumps, controls, and processing equipment are often decades old, and most lack manuals or digital troubleshooting resources. The knowledge needed to set up and operate this equipment exists entirely in the heads of experts who have been doing the job for 20 or 30 years.  

For manufacturing leaders in food and beverage, this workforce crisis couldn't have come at a worse time. Today, the market itself is changing in ways that demand more expertise than ever.

See how Laminar is optimizing Unilever's Clean-in-Place.

A perfect storm: more complexity, fewer experts

Consumer behavior in food and beverage has fundamentally shifted, creating unprecedented operational challenges.

Consumer Behavior Changed Overnight

F&B is used to hero products. A brand was built around just a few of them that actually lasted across generations.  

Heinz Ketchup has been on shelves for six generations of consumers. These hero products succeeded because of factory floor heroes: the experienced operators who could run an entire plant on intuition honed over decades.

But, the notion of "hero product" is almost dead.  

Younger consumers actively seek variety, switching between products based on trending flavors and ingredients. They scrutinize what goes into their food and beverages, driving demand for transparency and constant innovation.

The result has been an explosion in SKU complexity — almost overnight.  

One sauce manufacturer we work with produces up to 3,000 different SKUs in a single plant. Instead of running one formulation for an entire week with minimal stress, the facility now has to execute 50 batches across 25 different SKUs in that same timeframe. Each batch requires different inputs, distinct cleaning cycles between shifts, and unique product changeover routines—all without the veteran expertise that once made this manageable.

Razor-Thin Margins, Zero Room for Error

At the same time, input costs, tariffs, regulations, and supply chain uncertainties continue pressuring profitability across the food and beverage industry.

Operating on razor-thin margins means productivity must increase even as the margin for error shrinks. Plant managers face relentless pressure to maximize OEE and extract every possible hour of uptime from each production line. Regulatory requirements for food safety have grown stricter, and the financial and reputational costs of recalls keep climbing.

On the factory floor, maintaining high line availability depends on optimizing every product changeover and cleaning cycle to minimize resource consumption and get equipment back into production quickly.  

The old approach — static recipes with built-in time buffers — can't deliver the efficiency modern operations require. Food and beverage manufacturers are asking smaller teams to manage exponentially more complexity while the institutional knowledge that once guided these decisions continues walking out the door.

Learn how Laminar is helping Top 10 F&B companies and more face these challenges.

Industry 4.0 and Digital Transformation haven’t fixed the expertise problem

Digital transformation has been positioned as manufacturing's solution for 15 years, with vendors now adding "AI" to the same offerings.  

While there's been progress in warehouse management, supply chain software, and predictive maintenance, most solutions still require significant human expertise to implement and maintain, with timelines stretching across months or years.

The automation initiatives that will succeed capture expert knowledge in algorithms and execute processes autonomously, adapting dynamically to conditions while maintaining quality and safety standards.  

Closed-loop automation will define the next generation of food and beverage manufacturing — particularly for the two processes that most impact line availability: clean-in-place cycles and product changeovers.

Why CIP and changeovers need a total makeover

Most manufacturing processes still run on fixed assumptions and buffers that have been institutionalized over time. A clean-in-place cycle runs for 30 minutes because the SOP specifies 30 minutes, and no one questions it because the expertise needed to adjust it for different recipes has walked out the door. Line startup procedures and product changeovers remain unchanged even when new SKUs could be run more efficiently, leaving productivity gains on the table.

Static Procedures Create False Control

This approach worked when experienced operators ran the line because they knew when to cut a cycle short and could sense when something was off. Procedures served as a baseline rather than a rigid rulebook, and knowledge transfer happened organically as veterans worked alongside newer team members.

Without that expertise, teams follow timers exactly — even when doing so wastes resources or causes unnecessary downtime. The response is predictable: add buffer time to every step. They over-clean and overuse chemicals because the alternative is a failed quality check or a food safety incident that shuts down the line.

The result is higher operating costs, longer CIP cycle times, increased water and chemical usage, and quality or safety risks that only surface after something goes wrong.

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From static to dynamic: real-time is a game changer

The fundamental constraint in CIP recipes and other production processes comes down to four variables: time, temperature, titer (chemical concentration), and turbulence (cleaning effectiveness).

The Constraint: Time, Temperature, Titer, Turbulence

Cleaning step durations are hard-coded into PLC programs based on measured values like temperature, flow, pH, and conductivity. Turbulence can't be measured intrinsically, so operators rely on periodic manual sampling and swabbing to verify that pipes and equipment are actually clean.  

The entire process runs on conductivity readings and educated guesses rather than direct knowledge of what's flowing through the pipes.

What If You Could See Inside the Pipe?

What if you could monitor the actual chemistry of the liquid inside stainless steel pipes in real-time and run a self-adjusting process based on that data?

This is the Laminar answer.  

We flipped the script with our in-line spectral sensors that actively the orchestrate processes in real-time and self-correct each process cycle (like CIP, Changeovers, Batch Mixing etc.) to be optimal automatically.  

Instead of relying on operator intuition or chemical supplier recommendations, the science drives the process. We're executing this approach at scale in facilities operated by the world's largest food and beverage manufacturers, lowering downtime, increasing productivity, and reducing chemical and water usage.

How science-led automation improves agility and productivity

CIP Example: Monitor and Optimize Every Sub-Step

Take a typical clean-in-place cycle.  

Take a typical clean-in-place cycle. Instead of running rinse cycles until a timer expires or dosing caustic at high concentrations well above conductivity setpoints, Laminar's patented spectral sensors and machine learning models monitor each sub-step and optimize them individually.  

Laminar’s clean-in-place model identifies when pre-rinse or final-rinse steps are running longer than needed, corrects chemical concentration and cycle duration to reduce waste, and prevents CIP underwash by alerting operators to extend a step when necessary.  

The CIP process runs on the actual chemical composition of what's flowing through the pipe rather than proxy measurements like conductivity alone.

CIP cycles complete faster while still meeting quality benchmarks, and product changeovers adjust based on current conditions rather than worst-case timing estimates.  

The result is more product filled in each production run.

Learn more about Laminar Clean-in-Place Optimization

This data-driven automation removes the pressure on operators to make perfect decisions every time. When processes self-correct based on real-time chemistry, a new hire doesn't need thirty years of experience to avoid costly mistakes. The CIP models catch errors that previously required veteran intuition.

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Where Closed-loop, AI and automation delivers results

Food and beverage companies that adopt sensor-driven automation see measurable results.  

20% Faster Cycles, 15% More Line Availability

One global beverage manufacturer reduced average CIP cycle times by 20 percent after implementing Laminar's real-time monitoring and automated adjustments. Water consumption and chemical usage both declined while throughput increased. Line availability jumped 15 percent per shift.

These gains matter for sustainability targets and regulatory compliance alike.  

Demonstrating precise control over cleaning and sanitation processes strengthens food safety documentation. Reducing resource consumption supports environmental commitments. Self-documenting, digital batch records provides the data that regulators and manufacturer’s themselves increasingly expect.

For plant managers, the operational benefits are equally significant. Daily line availability becomes become more predictable which results in consistent output. Quality outcomes stabilize.  

Teams spend less time troubleshooting and more time on higher-value work. New hires ramp up faster because the production system provides guardrails that reduce the learning curve.

Science-Led, AI for manufacturing isn't the future—it's happening now

Retiring expertise, workforce shortages, SKU proliferation, tighter sustainability targets — these pressures will not ease. The food and beverage industry must adapt.

The facilities that thrive will be those that stop trying to replicate the workforce of the past. They will build processes that deliver consistent results without depending on scarce expertise. They will use easily deployable automation to capture and act on the kind of real-time intelligence that experienced operators once provided intuitively.

Knowledge loss in the food and beverage industry is a structural challenge. The response must be structural as well. Sensor-driven, real-time, closed-loop automation offers a path forward — one that protects quality, supports compliance, reduces waste, and makes operations more resilient to the workforce challenges ahead.

See What You're Missing

Most plants don't know how much time and resources they lose to buffer cycles and manual guesswork — until they measure it.

Our Clean-in-Place Savings Finder shows you where sensor-driven automation could reduce waste in your facility. Answer a few questions about your current operations, and you'll get a custom estimate of potential savings in water, chemicals, and cycle time.

See why you can't afford to run your CIP without Laminar. Try our no-commitment CIP Savings Finder below.

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